code: def _tolerance(X, rtol):
      """Compute absolute tolerance from the relative tolerance"""
      if rtol == 0.0:
          return rtol
      if sp.issparse(X):
          variances = mean_variance_axis(X, axis=0)[1]
          mean_var = np.mean(variances)
      else:
          mean_var = np.var(X, axis=0).mean()
      return mean_var * rtol
  
imports: import numbers
  import warnings
  import numpy
  from scipy import sparse
  from sklearn.cluster import KMeans
  from sklearn.cluster._kmeans import _labels_inertia
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.utils import check_array, check_random_state
  from sklearn.utils._openmp_helpers import _openmp_effective_n_threads
  from sklearn.utils.extmath import row_norms
  from sklearn.utils.sparsefuncs import mean_variance_axis
  from sklearn.utils.validation import _deprecate_positional_args, _num_samples, check_is_fitted
  import daal4py
  from .._device_offload import support_usm_ndarray
  from .._utils import PatchingConditionsChain, control_n_jobs, getFPType, run_with_n_jobs, sklearn_check_version
label_desc: Use image node_id 2 for calling a global function with example usage: _tolerance(X, rtol) and returns: unknown, rtol